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Updated: Oct 23, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Associations between brain abnormalities and common genetic variants for schizophrenia: a narrative review of
Zixuan Lin1, Yicheng Long1, Zhipeng Wu1
1National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.
Abstract:
Schizophrenia is a common psychotic disease worldwide, and several genetic variants have been suggested to influence susceptibility to schizophrenia. However, the exact genetic and neural mechanisms underlying such relationships remain unclear. Neuroimaging endophenotypes have been considered to be desirable for finding genes influencing brain structure and function. Because of its high penetrance of genetic variants and wide applications in clinic practice, neuroimaging could be a great option in schizophrenia study. In this narrative review, we aim to provide a summary of current progress in neuroimaging findings to detect genetic variants that may influence the brain's structure and function, and thus improve understanding of how this interaction affects the onset of schizophrenia. Multiple common genetic variants for schizophrenia including the ZNF804A, DTNBP1, DAOA, AKT1, NTRK3, and ERBB4 genes are reviewed. In summary, the current investigations have reported effects of these genetic variants on both structural and functional brain abnormalities (e.g., altered grey matter volumes, white matter integrity and functional connectivity patterns) in schizophrenia within multiple brain regions, especially the frontal, temporal and hippocampal areas. These findings facilitate our understanding of schizophrenia and helping us with early diagnosis, prognosis prediction and medication. However, a deep insight into this field necessitate further investigations and there are a number of challenges to be settled, such as enlarging the sample size; solving the statistical, methodological, and technological limitations; performing not only cross-sectional but also longitudinal observations; focusing on the effect of copy number variants; figuring out the complexity of epistasis and gene-environment interaction; achieving clinical translations; and depict the effect of a polygenic risk score beyond those of single genetic markers.
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